get ( timeout = 1 )) # prints the PID of that process # launching multiple evaluations asynchronously *may* use more processes multiple_results = print () # make a single worker sleep for 10 secs res = pool. getpid, ()) # runs in *only* one process print ( res. get ( timeout = 1 )) # prints "400" # evaluate "os.getpid()" asynchronously res = pool. apply_async ( f, ( 20 ,)) # runs in *only* one process print ( res. imap_unordered ( f, range ( 10 )): print ( i ) # evaluate "f(20)" asynchronously res = pool. map ( f, range ( 10 ))) # print same numbers in arbitrary order for i in pool. Forįrom multiprocessing import Pool, TimeoutError import time import os def f ( x ): return x * x if _name_ = '_main_' : # start 4 worker processes with Pool ( processes = 4 ) as pool : # print "" print ( pool. The if _name_ = '_main_' clause of the main module. To select a start method you use the set_start_method() in Named semaphores, and shared memory segments occupy some space in the main Problematic for both objects because the system allows only a limited number of Memory segments will be automatically unlinked until the next reboot. Usually there should be none, but if a process was killed by a signal Have exited the resource tracker unlinks any remaining tracked object. System resources (such as named semaphores orīy processes of the program. Start a resource tracker process which tracks the unlinked named On Unix using the spawn or forkserver start methods will also
NoĪvailable on Unix platforms which support passing file descriptorsĬhanged in version 3.4: spawn added on all unix platforms, and forkserver added forĬhild processes no longer inherit all of the parents inheritable Threaded so it is safe for it to use os.fork(). Is needed, the parent process connects to the server and requests When the program starts and selects the forkserver start method,Ī server process is started. Note that safely forking aĪvailable on Unix only. The child process, when it begins, is effectively The parent process uses os.fork() to fork the Python Rather slow compared to using fork or forkserver.Īvailable on Unix and Windows. Unnecessary file descriptors and handles from the parent process TheĬhild process will only inherit those resources necessary to run The parent process starts a fresh python interpreter process. So that child processes can successfully import that module. The followingĮxample demonstrates the common practice of defining such functions in a module Parallelizing the execution of a function across multiple input values,ĭistributing the input data across processes (data parallelism). Pool object which offers a convenient means of
The multiprocessing module also introduces APIs which do not haveĪnalogs in the threading module. Leverage multiple processors on a given machine. To this, the multiprocessing module allows the programmer to fully Offers both local and remote concurrency, effectively side-stepping the Multiprocessing is a package that supports spawning processes using anĪPI similar to the threading module. Multiprocessing - Process-based parallelism ¶
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